class_docstr: Class for the positive reals metric.
  
  It is a particular case in dimension 1
  of the SPD affine-invariant metric
  with a power affine coefficient equal to one.
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docstr: Compute the positive reals logarithm map.
  
  Compute the Riemannian logarithm at point base_point,
  of point wrt the positive reals metric.
  This gives a tangent vector at point base_point.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      Point.
  base_point : array-like, shape=[..., 1]
      Base point.
  
  Returns
  -------
  log : array-like, shape=[..., 1]
      Riemannian logarithm.
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code: def log(point, base_point):
      """Compute the positive reals logarithm map.
  
      Compute the Riemannian logarithm at point base_point,
      of point wrt the positive reals metric.
      This gives a tangent vector at point base_point.
  
      Parameters
      ----------
      point : array-like, shape=[..., 1]
          Point.
      base_point : array-like, shape=[..., 1]
          Base point.
  
      Returns
      -------
      log : array-like, shape=[..., 1]
          Riemannian logarithm.
      """
      return base_point * gs.log(point / base_point)
  
file_path: geomstats/geomstats/geometry/positive_reals.py
imports: import geomstats.backend
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
label_desc: Use image node_id 3 for calling the PositiveRealsMetric obj's underlying member method code with example usage: obj.log(point, base_point) and returns: unknown